The phrase "average absolute percentage" is correct and usable in written English.
It can be used in contexts involving statistical analysis or data evaluation, particularly when discussing the accuracy of predictions or measurements.
Example: "The average absolute percentage error in our forecasts was significantly lower this quarter compared to the last."
Alternatives: "mean absolute percentage" or "average absolute rate".
The average absolute percentage change of the Standard & Poor's 500-stock index (or the S.& P. composite, as it was once known) was just 1.46percentt.
The former algorithms gave an average absolute percentage deviation up to 5% whereas deviations up to 20% are obtained from the latter algorithms.
The results indicate that the developed model is able to estimate oil viscosity with an average absolute percentage relative error of 4.47%.
The overall average absolute percentage deviation for the calculation of the apparent reaction rate constant by this model is about 3.0%.
Secondly, a generalised neural network was trained to predict fibre diameter with an average absolute percentage error of 22.3% for the validation data.
Approximately zero value of average absolute percentage relative error (AAPRE = 0.76 %) recorded indicates relative low absolute deviation in percent from the experimental values.
For example, the results from the public holidays in France showed an average mean absolute percentage error (MAPE) of 0.863%, and the accuracy improvements over a simple average combination method, the best individual method, and a weighted combination are 15.887%, 13.353%, and 3.034%, respectively.
The LMFF model was able to improve the average of root mean square error (RMSEave) and average of mean absolute percentage error (MAPEave) values of the multiple linear regression forecasts by about 18% and 21%, respectively.
> -wrap-foot> Abbreviations: MA, moving average; MAPE, mean absolute percentage error.
In particular, the upper third of Table 1 presents averages of mean absolute percentage error (MAPE) estimates from M = 50 replications of the same out-of-sample prediction exercises for six benchmark procedures.
Panel (a) visualizes the differences between the (averaged) cross-city mean absolute percentage error estimates for g) together with Eq. 3a and fitted with regularization and the corresponding estimates for c).
